NIST deprecates RSA-2048 from 2030. Find every one of them before attackers do.
🐍
🐍 PyPI
Not in CISA KEV
MEDIUM severity

CVE-2022-35998 — tensorflow

MEDIUMFix: tensorflow/tensorflow@c8ba76d

CVE-2022-35998 is a medium-severity (CVSS 5.9) Reachable Assertion vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

`CHECK` fail in `EmptyTensorList` in TensorFlow

Also known asBIT-tensorflow-2022-35998GHSA-qhw4-wwr7-gjc5PYSEC-2026-937
Published
Updated
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed
Exploitation data as of Nov 4, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs42th percentile — riskier than 42% of all scored CVEsHighest risk
0.00%0.33%0.66%0.99%0.1%0.5%May 26Sep 26Nov 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

3 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.

import tensorflow as tf

tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32)

Patches

We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Kang Hong Jin.

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.7.2pip install --upgrade 'tensorflow==2.7.2'
🐍PyPItensorflow≥ 2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow==2.8.1'
🐍PyPItensorflow≥ 2.9.0&&< 2.9.12.9.1pip install --upgrade 'tensorflow==2.9.1'

Affected Products

1 product · 7 configurations
Application
tensorflowgoogle
≥ 2.9.0 && < 2.9.1
1 version
2.10

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update tensorflow to 2.7.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-35998 is resolved across your whole dependency graph.

  3. Workarounds

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

### Impact If `EmptyTensorList` receives an input `element_shape` with more than one dimension, it gives a `CHECK` fail that can be used to trigger a denial of service attack. ```python import tensorflow as tf tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32) ``` ### Patches We have patched the issue in GitHub commit [c8ba76d48567aed347508e0552a257641931024d](https://github.com/tensorflow/tensorflow/commit/c8ba76d48567aed347508e0552a257641931024d). The fix will be included in TensorFlow 2.10.0. We will als
O3 Security · Impact-Aware SCA

Is CVE-2022-35998 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2022-35998: tensorflow DoS — Fixed in 2.7.2